Occlusion-Aware Vehicle Navigation at Hidden Road Entrances
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating safely and accurately, particularly in identifying pedestrian and vehicle occlusion zones, hidden road entrances, and responding to dynamic environmental changes without relying solely on human input.
Innovation Solution
The implementation of a navigation system that utilizes cameras to analyze images, combined with GPS and sensor data, to identify occlusion zones and induce navigational changes, such as steering, braking, or acceleration, based on the presence and type of occluding objects, and their velocities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle uses camera-based image analysis to identify occlusion zones, then the navigation safety is improved, but the detection precision is reduced due to hidden road entrances and occluding objects
Solution Approach 1:
The system performs preliminary identification of occlusion zones and hidden road entrances using camera images before making navigation decisions. By detecting occluding objects and predicting potential hazards in advance, the system compensates for limited visibility and maintains detection precision despite occlusions.
Solution Approach 2:
The system introduces map data and location information as intermediary elements to supplement camera-based detection. By combining real-time image analysis with pre-stored map information about road entrances and intersections, the system achieves more accurate detection of hidden hazards that cameras alone cannot detect.
2Reliability
If the autonomous vehicle analyzes multiple images and sensor data to identify occlusion zones, then the navigation reliability is improved, but the device complexity increases
Solution Approach 1:
The processing device performs multiple functions using a single integrated system: it captures images from cameras, retrieves map data, identifies occlusion zones, detects hidden road entrances, and generates navigation commands. This multi-functional approach improves reliability through data fusion while avoiding the complexity of separate dedicated systems for each function.
Solution Approach 2:
The system merges camera image analysis, map data processing, and navigation decision-making into a single integrated processing device. By combining these functions that operate on different data types (images, map information, sensor data), the system achieves high reliability through complementary information while maintaining manageable complexity through unified processing.
3Object-affected harmful factors
If the autonomous vehicle responds to occlusion zones by causing navigational changes, then the accident risk is reduced, but the loss of time occurs due to frequent steering, braking, or acceleration adjustments
Solution Approach 1:
The system dynamically adjusts navigation commands based on the type and severity of detected occlusion zones. Rather than applying fixed conservative responses, the system generates adaptive navigational changes that are proportional to the detected hazard level, reducing unnecessary adjustments and time loss while maintaining safety.
Solution Approach 2:
The system performs preliminary analysis of occlusion zones to predict potential hazards before they become immediate threats. By identifying occluding objects and hidden road entrances in advance and planning navigation paths proactively, the system reduces the need for frequent emergency adjustments, thereby minimizing time loss while maintaining accident risk reduction.
Data Source
AI summary
A navigation system for a host vehicle is provided. The system may comprise at least one processing device programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify at least one vehicle-induced occlusion zone in an environment of the host vehicle; and cause a navigational change for the host vehicle based, at least in part, on a size of a target vehicle that induces the identified occlusion zone.